Todays model-based dynamic positioning (DP) systems require that the s
hip and thruster dynamics are known with some accuracy in order to use
linear quadratic optical control theory. However, it is difficult to
identify the mathematical model of a dynamically positioned (DP) ship
since the ship is not persistently excited under DP. In addition the s
hip parameter estimation problem is nonlinear and multivariable with o
nly position and thruster state measurements available for parameter e
stimation. The process and measurement noise must also be modeled in o
rder to avoid parameter drift due to environmental disturbances and se
nsor failure. This article discusses an off-line parallel extended Kal
man filter (EKF) algorithm utilizing two measurement series in paralle
l to estimate the parameters in the DP ship model. Full-scale experime
nts with a supply vessel are used to demonstrate the convergence and r
obustness of the proposed parameter estimator.